DestinyNet: A deep-learning framework for cell-fate analysis from lineage-tracing single-cell RNA sequencing data [0.03%]
命运网络：单细胞RNA测序谱系追踪的细胞命运分析深度学习框架
Zuozhu Liu,Songtao Jiang,Tianxiang Hu et al.
Zuozhu Liu et al.
Unraveling cell-development dynamics, including lineage commitment, differentiation, and disease progression, is fundamental to biology. Despite advances in single-cell omics and barcoding technologies, comprehensive frameworks for accurate...
BDI-Kit: An AI-powered toolkit for biomedical data harmonization [0.03%]
基于人工智能的生物医学数据标准化工具包(BDI-Kit)
Roque Lopez,Aécio Santos,Christos Koutras et al.
Roque Lopez et al.
The wide availability of biomedical data, coupled with advanced analytics, holds unprecedented promise for scientific discovery and improved patient care; yet, heterogeneity across datasets remains a major barrier. Given the inherent divers...
Wojtek Treyde,Aleksy Kwiatkowski,Jascha Achterberg et al.
Wojtek Treyde et al.
The Science through Computation Initiative unites sixteen early-career computational scientists spanning physics, biology, chemistry, and neuroscience. Over nine months of workshops and hackathons, they agreed on "computational motifs," fun...
A label masked autoencoder for image-guided segmentation label completion [0.03%]
一种用于图像引导的分割标签补全的掩膜自动编码器方法
Jiaru Jia,Mingzhe Liu,Dongfen Li et al.
Jiaru Jia et al.
Recent studies have demonstrated that high-quality annotated data are crucial for segmentation performance. However, incomplete or corrupted mask annotations remain common, limiting supervised learning. To address this, we introduce a mask-...
Confidence-weighted integration of human and machine judgments for superior decision-making [0.03%]
基于人类和机器判断的自信加权集成决策方法
Felipe Yáñez,Xiaoliang Luo,Omar Valerio Minero et al.
Felipe Yáñez et al.
Large language models (LLMs) can surpass humans in certain forecasting tasks. What role does this leave for humans in the overall decision process? One possibility is that humans, despite performing worse than LLMs, can still add value when...
Contrastive learning enables epitope overlap predictions for targeted antibody discovery [0.03%]
对比学习能够进行表位重叠预测以发现目标抗体
Clinton M Holt,Alexis K Janke,Parastoo Amlashi et al.
Clinton M Holt et al.
Computational epitope prediction remains an unmet need for therapeutic antibody development. We present three complementary approaches for predicting epitope relationships from antibody sequences. First, by analyzing approximately 18 millio...
Michael F Gensheimer
Michael F Gensheimer
Many oncology predictive models fail to improve care. Issues include risks of bias, underpowered radiomics studies, and limited clinical impact. A path forward involves an emphasis on clinically actionable questions, rigor, and generalizabi...
Embeddings from language models are good learners for single-cell data analysis [0.03%]
语言模型嵌入是单细胞数据分析的良好学习器
Tianyu Liu,Tianqi Chen,Wangjie Zheng et al.
Tianyu Liu et al.
Foundation models (FMs) have been built to analyze single-cell data with different degrees of success. Here, we present scELMo (single-cell embedding from language models), a method for analyzing single-cell data with the help of large lang...
A self-supervised framework for emphysema anomaly detection and staging in computed tomography scans [0.03%]
一种自我监督的框架用于计算机断层扫描中的肺气肿异常检测和分期
Xiang Zhang,Mingyue Zhao,Fei Yao et al.
Xiang Zhang et al.
Emphysema, a diffuse and heterogeneous phenotype of chronic obstructive pulmonary disease (COPD), carries substantial morbidity and elevates lung cancer risk. While computed tomography (CT) aids in detection and monitoring, current deep lea...
Leveraging protein language models and a scoring function for indel characterization and transfer learning [0.03%]
利用蛋白质语言模型和评分函数进行插入删除特征分析和迁移学习
Oriol Gracia Carmona,Vilde Leipart,Gro V Amdam et al.
Oriol Gracia Carmona et al.
Protein language models (PLMs) are increasingly used to assess the impact of genetic variants, achieving high accuracy and often outperforming traditional pathogenicity predictors. They enable zero-shot inference, making predictions without...